Bioinformatics for vaccinology


    • Flower, Darren R.


Bioinformatics for vaccinology

Darren R. Flower

Wiley-Blackwell, 2008

  • : pbk

大学図書館所蔵 件 / 2



Includes bibliographical references and index



"...this book was written from start to finish by one extremely dedicated and erudite individual. The author has done an excellent job of covering the many topics that fall under the umbrella of computational biology for vaccine design, demonstrating an admirable command of subject matter in fields as disparate as object-oriented databases and regulation of T cell response. Simply put, it has just the right breadth and depth, and it reads well. In fact, readability is one of its virtues-making the book enticing and useful, all at once..." Human Vaccines, 2010 "...This book has several strong points. Although there are many textbooks that deal with vaccinology, few attempts have been made to bring together descriptions of vaccines in history, basic bioinformatics, various computational solutions and challenges in vaccinology, detailed experimental methodologies, and cutting-edge technologies...This book may well serve as a first line of reference for all biologists and computer scientists..." -Virology Journal, 2009 Vaccines have probably saved more lives and reduced suffering in a greater number of people than any other medical intervention in human history, succeeding in eradicating smallpox and significantly reducing the mortality and incidence of other diseases. However, with the emergence of diseases such as SARS and the threat of biological warfare, vaccination has once again become a topic of major interest in public health. Vaccinology now has at its disposal an array of post-genomic approaches of great power. None has a more persuasive potential impact than the application of computational informatics to vaccine discovery; the recent expansion in genome data and the parallel increase in cheap computing power have placed the bioinformatics exploration of pathogen genomes centre stage for vaccine researchers. This is the first book to address the area of bioinformatics as applied to rational vaccine design, discussing the ways in which bioinformatics can contribute to improved vaccine development by introducing the subject of harnessing the mathematical and computing power inherent in bioinformatics to the study of vaccinology putting it into a historical and societal context, and exploring the scope of its methods and applications. Bioinformatics for Vaccinology is a one-stop introduction to computational vaccinology. It will be of particular interest to bioinformaticians with an interest in immunology, as well as to immunologists, and other biologists who need to understand how advances in theoretical and computational immunobiology can transform their working practices.


CONTENTS Preface Acknowledgements Exordium: Vaccines: a Very, Very Short Introduction 1 Vaccines: Their Place in History Smallpox in History Variolation Variolation in History Variolation Comes to Britain Lady Mary Wortley Montagu Variolation and the Sublime Porte The Royal Experiment The Boston Connection Variolation Takes Hold The Suttonian Method Variolation in Europe The Coming of Vaccination Edward Jenner Cowpox Vaccination Vindicated Louis Pasteur Vaccination Becomes a Science Meister, Pasteur, and Rabies A Vaccine for Every Disease In the Time of Cholera Haffkine and Cholera Bubonic Plague The Changing Face of Disease Almroth Wright and Typhoid Tuberculosis, Koch, and Calmette Vaccine BCG Poliomyelitis Salk and Sabin Diptheria Whooping Cough Many Diseases, Many Vaccines Smallpox: Endgame Further Reading 2 Vaccines: Need and Opportunity Eradication and Reservoirs The Ongoing Burden of Disease Lifespans The Evolving Nature of Disease Economics, Climate, and Disease Three Threats Tuberculosis in the 21st Century HIV and AIDS Malaria: Then and Now Influenza Bioterrorism Vaccines as Medicines Vaccines and the Pharmaceutical Industry Making Vaccines The Coming of the Vaccine Industry 3 Vaccines: How They Work Challenging the Immune System The Threat from Bacteria: Robust, Diverse, and Endemic MiCrobes, Diversity, and Metagenomics The Intrinsic Complexity of the Bacterial Threat Microbes and Humankind The Nature of Vaccines Types of Vaccine Carbohydrate Vaccines Epitopic Vaccines Adjuvants and Vaccine Delivery Emerging Immunovaccinology The Immune System Innate Immunity Adaptive Immunity The Microbiome and Mucosal Immunity Cellular Components of Immunity Cellular Immunity The T Cell Repertoire Epitopes: The Immunological Quantum The Major Histocompatility Complex MHC Nomenclature Peptide Binding by the MHC The Structure of the MHC Antigen Presentation The Proteasome Transporter Associated with Antigen Processing Class II Processing Seek Simplicity and Then Distrust It Cross Presentation T Cell Receptor T Cell Activation Immunological Synapse Signal 1, Signal 2, Immunodominance Humoral Immunity Further Reading 4 Vaccines: Data and Databases Making Sense of Data Knowledge in a Box The Science of -Omes and -Omics The Proteome Systems Biology The Immunome Databases and Databanks The Relational Database The XML Database The Protein Universe Much Data, Many Databases What Proteins Do What Proteins Are The Amino Acid World The Chiral Nature of Amino Acids Naming the Amino Acids The Amino Acid Alphabet Defining Amino Acid Properties Size, Charge, and Hydrogen Bonding Hydrophobicity, Lipophilicity, and Partitioning Understanding Partitioning Charges, Ionization, and pKa Many Kinds of Property Mapping the World of Sequences Biological Sequence Databases Nucleic Acid Sequence Databases Protein Sequence Databases Annotating Databases Text Mining Ontologies Secondary Sequence Databases Other Databases Databases in Immunology Host Databases Pathogen Databases Functional Immunological Databases Composite, Integrated Databases Allergen Databases Further Reading Reference 5 Vaccines: Data Driven Prediction of Binders, Epitopes and Immunogenicity Towards Epitope-Based Vaccines T Cell Epitope Prediction Predicting MHC Binding Binding is Biology Quantifying Binding Entropy, Enthalpy, and Entropy-Enthalpy Compensation Experimental Measurement of Binding Modern Measurement Methods Isothermal Titration Calorimetry Long and Short of Peptide Binding The Class I Peptide Repertoire Practicalities of Binding Prediction Binding Becomes Recognition Immunoinformatics Lends a Hand Motif Based Prediction The Imperfect Motif Other Approaches to Binding Prediction Representing Sequences Computer Science Lends a Hand Artificial Neural Networks Hidden Markov Model Support Vector Machines Robust Multivariate Statistics Partial Least Squares Quantitative Structure Activity Relationships Other Techniques and Sequence Representations Amino Acid Properties Direct Epitope Prediction Predicting Antigen Presentation Predicting Class II MHC Binding Assessing Prediction Accuracy Roc Plots Quantitative Accuracy Prediction Assessment Protocols Comparing Predictions Prediction Versus Experiment Predicting B Cell Epitopes Peak Profiles and Smoothing Early Methods Imperfect B Cell Prediction References 6 Vaccines: Structural Approaches Structure and Function Structure and Function Types of Protein Structure Protein Folding Ramachandran Plots Local Structures Protein Families, Protein Folds Comparing Structures Experimental Structure Determination Structural Genomics Protein Structure Databases Other Databases Immunological Structural Databases Small Molecule Databases Protein Homology Modelling Using Homology Modelling Predicting MHC Supertypes Application to Alloreactivity 3D-QSAR Protein Docking Predicting B Cell Epitopes with Docking Virtual Screening Limitations to Virtual Screening Predicting Epitopes with Virtual Screening Virtual Screening and Adjuvant Discovery Adjuvants and Innate Immunity Small Molecule Adjuvants Molecular Dynamics and Immunology Molecular Dynamics Methodology Molecular Dynamics and Binding Immunological Applications Limitations of Molecular Dynamics Molecular Dynamics and High Performance Computing References 7 Vaccines: Computational Solutions Vaccines and the World Bioinformatics and the Challenge for Vaccinology Predicting Immunogenicity Computational Vaccinology The Threat Remains Beyond Empirical Vaccinology Designing New Vaccines The Perfect Vaccine Conventional Approaches Genome Sequences Size of a Genome Reverse Vaccinology Finding Antigens The Success of Reverse Vaccinology Tumour Vaccines Prediction and Personalised Medicine Imperfect Data Forecasting and the Future of Computational Vaccinology Index

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